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FOOD:LAB
Strategic Oversight & Author: Tanner Methvin Contributor: Etai Even-Zahav | Editor: Tambudzai Ndlovu Project Management: Robin Jutzen & Tambudzai Ndlovu Design: Thandiwe Tshabalala | Photography: Yasser Booley ©Africa Centre 2015 | 5th Floor Exchange Building, 28 St George’s Mall, Cape Town |
[email protected] | www.africacentre.net All rights reserved. No part of this publication may be reproduced in any form or by any means without prior permission from the Africa Centre.
2
CONTENTS 5
Project Overview
20
Spaza Shops
7
Context
22
Kanana Residents
7
Everyday Urbanism
24
Kanana Overview
9
Food Security Lab
41
Perceptions of Behaviour
9
Background
65
Actual Behaviour
12
South Africa & Food Insecurity
92
Motivations for Behaviour
12
Urban Food Insecurity & Cape Town
132
Spaza Shops
15
Focus Area
146
Closing Remarks
18
Research Intentions
148
Acknowledgements
18
Research Structure
149
Bibliography
3
4
PROJECT OVERVIEW Everyday African Urbanism is a conceptual framework
they do; where they shop and how often; beyond resource
that filters out the macro picture of city life and instead
constraints, what influences their food purchasing choices;
focuses on the micro-spaces of everyday engagement
at what income level is it possible to secure a high quality
and interaction.
regular diet; and what are the environmental, social and psychological factors that may prevent a strategic approach
To re-imagine and re-define the meaning of urban life and
to food purchases and consumption? At the centre of this
plot a different future/s, we have to first understand what is
research was an exploration of how the local/immediate
actually going on through the practices of the people who
food suppliers (spaza shops1, street vendors, informal
live there. The Africa Centre has applied this framework to
cooking facilities) contribute to the food ecosystem. As
its initial intervention: The Food Security Lab.
such, the Lab also included an in depth review of the spaza shops in particular, the stock they carry and why, their
To date, The Food Security Lab has comprised 16 months of
supply chains and a range of consumer behaviour within
research within a community called Kanana in Gugulethu,
the shops.
Cape Town, South Africa. The research focused on how people living within households that generally earn a monthly income of R4,000 or less manage their food requirements. It examined: why they purchase the food
1.
Spaza Shops are informal general stores typically operating out of shacks outside the public sector’s regulatory framework.
5 5
6
CONTEXT Urbanisation can be defined as the rapid and
in the world today living in slums and the most
mental interventions that are flawed and which,
massive growth of, and migration to, large cit-
extreme depths of deprivation within these com-
by and large, are unable to come to terms with
ies. We are currently experiencing the second
munities. Cities and towns in Africa have been
the reality and implications of rapid urbanisation.
most important period of urban growth and
growing in tandem with slums and informal eco-
To support alternative approaches to the Conti-
transition in the history of the world and this
nomic activity.
nent’s urban development trajectory, a new body
process is almost entirely localised within the Global South.
of theory and practice must be considered. In In 2014 the United Nations reported 70% of Afri-
other words, unless we can imagine and develop
can urban dwellers live in slums and in SSA, only
a more credible account of everyday urbanism,
Statisticians have been measuring this transi-
30% of the population is linked to an electricity
the desire for urban improvement will remain a
tion since 1950 and expect it to continue until
network; 60% to portable water; and 31% have
frustrated yearning.
approximately 2030. Over this period the Global
access to sanitation. The reason Africa’s rapid
South is expected to grow the urban share of its
urbanisation has translated into the explosion
EVERYDAY URBANISM
populations from 18% to 60%.
of poverty, slum-living, and gross inequity is, of
A significant resource of literature dealing with
course, complex and manifold. One clear mate-
everyday urbanism asserts that we have to first
Although today 40% of Africa is officially urban-
rial issue that seems poorly understood within
understand what is actually going on through the
ised this figure hides enormous discrepancies
this complexity is the lack of competent theory,
practices of the people who live in urban spaces
across the continent - certain countries (all of
which underpins policies and programmes, and
before solutions are defined and implemented.
the large African economies) and regions have
effective implementation and governance of
The principle being that more often than not,
already reached the 50% mark while others lag
these programmes at multiple levels of public
theory is developed in the abstract and remains
far behind. However, the reality of African ur-
and private sector leadership - city, regional and
without practical application. How can we pos-
banisation disproves the generally accepted
national.
sibly expect to address the broad continuum
principle that economic prosperity is associ-
of challenges facing the urban poor if we don’t
ated with higher rates of urbanisation. In fact,
It is clear to us today that on one hand much of
have an intimate understanding of their desires,
Sub-Sahara Africa (SSA) which represents over
public and private sector leadership in Africa is
aspirations, attachments, connectivity, and mo-
90% of the continent, has the largest population
using policy frameworks and social and environ-
tivations?
7 7
8
FOOD SECURITY LAB To bring the ideas of Everyday Urbanism into
of chronic undernourishment of 209 million be-
ent countries would be possible. In the process,
practice, as a means of understanding a specif-
tween today and 1990-1992 .
they are inherently forced to make broad estima-
1
ic aspect of urban behaviour we designed the Food Security Lab research initiative.
tions and to omit a range of important details. Yet, these big statistics tell a partial story. The
These span from macro-trends to intra-regional
number of people suffering from poverty and
variations, to micro-scale, context-specific coping
It is our intention that the information and knowl-
hunger remains unacceptably high after dec-
strategies.
edge generated out of this process will support
ades of development efforts: 1.2 billion people are
policy, programmes and solutions to the food se-
still estimated to be trapped in extreme poverty,
Hunger, or more technically ‘undernutrition’, of-
curity challenges facing our country.
1
while 805 million are chronically undernourished
fers a pertinent example of a simplified measure
BACKGROUND
.Meanwhile, there is enough wealth and food in
that only tells a small part of a complex story – im-
global circulation to support humanity adequate-
portant as it is. Inadequate nutrition, or ‘malnutri-
The Millennium Development Goals (MDGs)
ly. It is global disparities, not insufficient resources
tion’ manifests in often invisible and counter-intu-
placed the need to “eradicate extreme poverty
that are fundamentally implicated in this human
itive ways. For instance, ‘micronutrient deficiency’
and hunger” by 2015 at the top of the interna-
development crisis. Secondly, these statistics do
or ‘invisible hunger’, a deficiency in vitamins and/
tional community’s agenda to improve the grim
not disclose inter-regional differences. Nearly all
or minerals in the body, affects a large portion
state of human health, equity and dignity.
of the globe’s destitute and hungry citizenry re-
of the world population, with adverse effects on
side in the Global South. Even within the Global
human wellbeing. Another relatively recent and
On both accounts, that is, poverty and hunger,
South, wide disparities exist. Sub-Saharan Afri-
counter-intuitive form of malnutrition, ‘over-nutri-
there have been encouraging gains in recent
ca for instance fares particularly poorly on both
tion’, is commonly believed to manifest in over-
years. The MDGs indicate that there were 700 mil-
scores compared to the rest of the Global South.
weight and obesity. Globally between 1980 and
lion less people living in extreme poverty in 2010
Thirdly, because the MDGs cover such a wide
2013 the number of overweight and obese people
as in 1990. Likewise, the latest Food and Agricul-
suite of developmental issues, the measures used
is estimated to have increased from 857 million to
ture Organisation’s (FAO) report on the State of
to assess progress have to be simple and well-
2.1 billion3. Overweight and especially obesity car-
Food Insecurity in the World shows a reduction
established, so that retrieving data across differ-
ry particularly deleterious consequences, ranking
&2
1. 2. 3.
FAO (2014) MDGs (2013:11) Ng et al. (2014)
9 9
amongst the top non-communicable health risks.
for an active and healthy life”5. From this defi-
energy dense, high fat, high protein, nutrient poor,
While traditionally these phenomena were closely
nition, four key pillars can be distilled, namely,
highly processed, high in sugar foods. These food
associated with wealth and the Global North, the
“food availability, physical and economic access
choices are informed by the increased demands
rate of the ‘pandemic’ is now growing dramati-
to food, utilisation and stability over time” .
put on urban residents’ time, which leads to the
5
cally in the Global South.
purchase of cheaper ready made foods, which are Mega-trends, such as the second wave of urbani-
defined by these qualities.
Unlike undernourishment – where some major im-
sation along with economic globalisation are chal-
provements have been made and there are best-
lenging conventional conceptions of food secu-
However, since much of the Global South is still
practice examples to draw on – with obesity there
rity. Traditionally, food security focused narrowly
struggling with widespread under nutrition, its
are “…no national success stories” since 1980 as
on reducing hunger and improving availability by
urban centres are increasingly seeing a disturb-
reported by Ng et al. (2014). There are numerous
increasing rural food production levels. To date, a
ing co-existence of overweight and obesity. This
factors with direct causal links to obesity ranging
clear ‘rural bias’ persists. However, as the Global
stark ‘double burden’ of malnutrition facing
from excessive calorie intake (over-nutrition), to
South urbanises rapidly, securing urban access
many urban hubs across the African continent
dietary changes, decreased physical activity and
to not only sufficient but also nutritious food, is
and other parts of the Global South demands
increasingly, changes in gut microbiome.
becoming a fast-growing but neglected prob-
integrated approaches that examine and deal
lem . Urbanisation, economic globalisation and
with food security, and health more generally in
Food security looks beyond hunger; “…not as a
concomitant food-chain consolidation (from pro-
all its dimensions.
deficit of calories, but as a violation of a broader
ducers through to retailers ) are initiating a ‘nutri-
set of social, economic and physical conditions” .
tion transition’8. Put crudely, this term describes
It speaks to a wide range of requirements need-
the shifting of diets that occurs as people switch
ed to create an enabling environment where “all
from an ‘agrarian’ rural to a more urban ‘industri-
people, at all times, have physical and economic
alised’ lifestyle. This shift can, in a small measure,
access to sufficient, safe and nutritious food to
be associated with a more sedentary lifestyle, but
meet their dietary needs and food preferences
is likely more related to increased consumption of
6
4
4. 5. 6. 7. 8.
Patel (2012:2) FAO (2014) Frayne et al. (2014) Reardon & Timmer (2007) Popkin et al. (2012)
7
10 10
11
SOUTH AFRICA & FOOD INSECURITY
intake’ in the Survey “…reflects the classic picture
on poor households as they tend to be the most
of the nutrition transition and urbanisation” . While
food insecure. Their baseline study found that 77%
South Africa offers a telling case-study of this dou-
the intricacies of this Survey are far more sophisti-
of the surveyed households were moderately or
ble burden and the necessity of developing an in-
cated than it can be given credit for here, the key
severely food insecure. In Cape Town, which was
tegrated two-pronged approach to food security
conclusion is that South Africa faces a related nu-
one of the 11 cities included in the studies, this rate
that addresses both under nutrition and obesity. It
tritional problem that needs to be tackled in an in-
was even higher, at 80%12. The informal settlement
is important to note that South Africa produces an
tegrated manner and customised to also cater for
of Khayelitsha fared particularly badly, with mod-
adequate supply of food nationally. Yet, clearly pro-
a fast-growing informal urban population. Despite
erate to severe food insecurity levels at 89%. This
ducing enough food does not automatically secure
the fact that South Africa is already 54% urban
study indicates the pervasiveness of the problem
access to it, financial or physical. South Africa’s Na-
(expected to reach 77% by 2050)
where access
and shows the urgency of confronting what it calls
tional Health and Nutrition Survey (SANHANES-1)9
is the main concern, direct food security interven-
the ‘invisible crisis’ of food insecurity among the
found that nationally, 26% of its population expe-
tions still focus almost exclusively on production.
urban poor.
rienced hunger while a further 28% were at risk of
9
10
areas, where 32% of the population was found to
URBAN FOOD INSECURITY & CAPE TOWN
be food insecure while 36% was at risk of hunger.
Looking at national data conceals disparities, es-
security in recent years. In 2013 the City of Cape
Notably, while the percentage of those experienc-
pecially in South Africa given its acute levels of so-
Town commissioned a Food System Study to in-
ing hunger has been halved since 1999, ‘at risk of
cio-economic inequality. Little attention is paid to
vestigate the contributions of particular areas to
hunger’ prevalence has slightly increased. In terms
the urban dimensions of food security. One excep-
urban agriculture as well as learn more about the
of obesity and overweight, measured by body mass
tion is the African Food Security Urban Network
food value chain. The study has yet to be released,
index (BMI), prevalence was significantly higher
(AFSUN), which conducted an 11-city study in 9
but its findings should enrich current knowledge
in females than in males (24.8% and 39.2% com-
Southern African Countries to evaluate the extent
and inform further interventions. However, there
pared to 20.1% and 10.6% for females and males,
11
of urban food insecurity . Unlike national studies
is still a significant paucity of research on the
respectively).
that survey the entire population, AFSUN focused
broader ‘food system’ in Cape Town; studies that
hunger. The situation was worse in urban informal
9. 10. 11. 12.
A further examination of ‘dietary
Shisana et al. (2013) UNDP (2014) Frayne et al. (2010) Battersby (2011)
12 12
Encouragingly, there seems to be a growing acknowledgement of the importance of urban food
evaluate the range of factors that influence food
the household income level of R4,000 per month
within a community. As such, gleaning an in-depth
security once it leaves the farm and before it ar-
manage their food requirements. Why do they pur-
understanding of what food is made available and
rives at the household. The effects of ‘Big Food’,
chase the food they do? Where do they shop, how
why, what spaza shop customers want, what food
the multinational food and beverage industry with
often? Beyond resource constraints, what influenc-
purchase choices they make, what influences these
huge and concentrated market power, are begin-
es their food purchase choices? What are the en-
decisions and how to change both what is sold and
ning to be documented, including work on food
vironmental, social and psychological factors that
what is consumed can potentially provide greater
deserts
and supermarket expansion . Even less
may be preventing a strategic approach to food
insight
research is available on the ‘small food’ actors and
purchases and consumption within these families?
South Africa.
their impact on community-level food security in
Understanding the answers to these questions and
informal settlements. These small actors include a
modelling alternative solutions to the existing food
broad spectrum of traditional as well as contem-
purchase and consumption paradigms, provided
porary mutations of micro-businesses and small
the motivation for creating the Food Security Lab
businesses, including spaza shops, independent
project.
13
14
food takeaways and street-food vendors. The Lab’s first manifestation focused on an inWe have scarcely begun to understand the ‘food
depth review of these questions through the lens
environment’ in the novel context of rapid urbani-
of the spaza shop. Spaza shops proliferate low-in-
sation and burgeoning informality in South Afri-
come communities in South Africa and often func-
ca. Little is understood about how people below
tion as a primary point of access to food sources
13. Battersby & Crush (2014) 14. Battersby & Peyton (2014)
13 13
into the food security challenges facing
14
MAP OF KANANA KANANA
FOCUS AREA The Food Security Lab research focused on an area called Kanana, a section of the larger community of Gugulethu in Cape Town. Kanana was chosen and identified as the site for this study because of its average household income, housing type, access to an urban centre, food retailers and the socio-demographics of the population. These conditions are similar to many other low-income communities within South African cities. While the research from this community cannot provide a direct blue print for every urban low-income community, it can progress our knowledge of what is driving food insecurity and support and inform other research and interventions in other areas.
MAP OF KANANA Kanana is comprised of 3,177 households, all of which are shacks; 90% have electricity and 1% have running water and formal ablution facilities in their backyards. It is primarily an isiXhosa speaking community with an average monthly household income of between R1,000 and R2,000.
15
AERIAL VIEW OF AERIAL VIEW OF KANANA
KANANA DURHEIN
KING DAVID COUNTRY CLUB
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16 16
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Courtesy of the City of Cape Town (2013)
->
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R3,201
Courtesy of the 2011 Census Courtesy of the 2011 Census Nearly 35.7% in the theCity CityofofCape Cape Town below the poverty lessR3,500 than R3500 (Census 2011) Nearly 35.7%of ofhouseholds households in Town livelive below the poverty line ofline lessof than
36
EMPLOYMENT STATUS OF EMPLOYMENT STATUS OF POPULATION
POPULATION
100% 90% 80% 70% 60% 50% 40%
46% EMPLOYED
28% UNEMPLOYED
30%
22%
NOT ECONOMICALLY ACTIVE
20%
4%
DISCOURAGED WORK-SEEKER
10% 0% EMPLOYMENT STATUS
EMPLOYMENT STATUS Courtesy of Stats SA (2014) Stats reports 25.5% of the population in South unemployed, with an unemployment rate of 23.9% rate in Cape Town. in Cape Town. StatsSA SA(2014) (2014) reports 25.5% of total the total population in Africa Southare Africa are unemployed, with an unemployment of 23.9%
37 37
PERCENTAGE WHO OWN A MOBILE PHONE
PERCENTAGE OF PARTICIPANTS WHO OWN A MOBILE PHONE
38
TIME IT TAKES TO TIME IT TAKES TO FETCH WATER FROM TAPS FETCH WATER FROM TAPS
71% 20%
4%
2%
2% 39
ENERGY ENERGYFOR FORCOOKING COOKING
ENERGY FOR LIGHTING ENERGY FOR LIGHTING
3%
2% 1%
97%
97%
Courtesy of Stats SA (2014)
Courtesy ofSAStats Courtesy of Stats (2014) SA (2014)
Courtesy Stats SA (2014) 94% of theof population in the City of Cape Town have electricity for lighting; 85.4% of South African homes have access to electricity Stats SA (2014) 94% of the population in the City of Cape Town have electricity for lighting; 85.4% of South African homes have access to electricity
40 40
PERCEPTIONS OF BEHAVIOUR The data reflected in this section is the result of personal interviews conducted by field workers from the community using a questionnaire on their mobile phones. Participants were also weighed and measured as part of the process so that body mass index scores could be determined. The interviews were conducted in various public spaces in Kanana.
41
GENDER
GENDER
46%
54%
MALE
FEMALE
42
AGE DISTRIBUTION AGE DISTRIBUTION
41%
AGE: 25 - 34 YRS
39%
AGE: 35 - 50 YRS
45% 40% 35% 30% 25% 20%
13%
7%
AGE: 18 - 24 YRS
AGE: > 51 YRS
15% 10% 5% 0%
43 43
BODY MASS INDEX (BMI) BODY MASS INDEX (BMI)
39%
45% 40%
23%
35% 30%
OVERWEIGHT BMI: 25 - 30
25% 20% 15% 10%
31%
NORMAL WEIGHT BMI: 18.5 - 25
7%
UNDERWEIGHT BMI: < 18.5
5% 0%
44
OBESE BMI: > 30
GENDER DISTRIBUTION ACROSS FOUR BMI CATEGORIES
GENDER DISTRIBUTION ACROSS FOUR BMI CATEGORIES
63%
70%
49%
60%
50%
40%
19%
30%
20%
10%
17%
29%
8% 3%
12%
0% UNDERWEIGHT UNDERWEIGHT (BMI: < 18.5) (< 18.5)
NORMAL WEIGHT NORMAL WEIGHT (BMI: 18.5 25) (18.5 - -25) 45 45
OVERWEIGHT OVERWEIGHT (BMI: 25 - 30) (25-30)
OBESE OBESE (BMI: > 30) (> 30)
PERCENTAGE OF PARTICIPANTS WHO GROW THEIR OWN FOOD
PERCENTAGE OF RESPONDENTS WHO GROW THEIR OWN FOOD
4% 46
REASONS GIVENGIVEN FOR NOT FOR GROWING FOOD REASONS NOT GROWING
FOOD
7% 1% 14%
62%
16%
47 47
WHERE FOOD IS PURCHASED WHERE FOOD IS PURCHASED
8% 15% 16% 16%
46% SPAZA
Spaza: Informal convenience shop; Large Grocery Store: Such as Shoprite or Pick n’ Pay Only; Hot Food Vendor: An informal kiosk that sells pre-cooked food; Spaza: Informal convenience shop; Large Grocery Chain: Such as Shoprite or Pick n’ Pay Only; Other: Unidentified source; Hot Food Vendor: An informal kiosk that sells Fruit & Veg stall: An open-air stall largely selling vegetables and fruit as well as small confectionary; Tshisanyama: Informal barbecue or braai typically located near pre-cooked food; Fruit & Veg stall: An open-air stall largely selling vegetables and fruit as well as small confectionary; Tshisanyama: Informal barbecue or braai typically a butchery to grill meat on an open fire. near a butchery to grill meat on an open fire
48
MAIN REASONS INFLUENCING FOOD PURCHASE CHOICE
MAIN REASONS INFLUENCING FOOD PURCHASE CHOICE
9% 49% 42%
49
MODE OF TRANSPORT USED TO GET TO FOOD OUTLETS MODE OF TRANSPORT USED TO GET TO FOOD OUTLETS
1% TRAIN
1% WALKING & TRAIN
95% WALKING
1% 50
2% WALKING & TAXI
AVERAGE AMOUNT SPENT ON FOOD PER WEEK
AVERAGE AMOUNT SPENT ON FOOD PER WEEK
R300
R277
R250
R200
R150
R100
R50
R0
51 51
AVERAGE AMOUNT SPENT WEEKLY ON FOOD
AVERAGE AMOUNT SPENT WEEKLY ONMONTHLY FOOD RELATED TO HOUSEHOLD MONTHLY INCOME RELATED TO HOUSEHOLD INCOME
R608
AVERAGE WEEKLY AVERAGE SPENT SPENT WEEKLY
R600 R600
R500 R500
R400 R400
R336
R300 R300
R200 R200
R386
R184
R272
R100 R100
R0 R0 R4000
AVERAGE AMOUNT SPENT WEEKLY ON FOOD AMOUNT RELATIVE EMPLOYMENT STATUS AVERAGE SPENTTO WEEKLY ON FOOD RELATIVE TO EMPLOYMENT STATUS
AVERAGE SPENT WEEKLY ON FOOD
AVERAGE SPENT WEEKLY ON FOOD
R323
R253
R350 R300 R250 R200 R150 R100 R50 R0
EMPLOYED
UNEMPLOYED EMPLOYMENT STATUS EMPLOYMENT STATUS
53
AVERAGE AMOUNT SPENT WEEKLY ON FOOD RELATIVE TO GENDER
AVERAGE AMOUNT SPENT WEEKLY ON FOOD RELATIVE TO GENDER
AVERAGE SPENT WEEKLY ON FOOD
AVERAGE SPENT WEEKLY ON FOOD
R300
R299
R260
R250
R200
R150
R100
R50
R0
MALE
FEMALE
54
RELATIONSHIP BETWEEN SHOPPING RELATIONSHIP BETWEEN SHOPPING FREQUENCY & HOUSEHOLD MONTHLY INCOME FREQUENCY AND HOUSEHOLD MONTHLY INCOME
36%
Household monthly income:
< R999
30% 46%
R1,000 - R2,000
52%
18%
18%
DAILY
Household monthly income:
WEEKLY
19%
MONTHLY
42%
Household monthly income:
R2,001 - R3,000
40%
18% 55 55
Household monthly income:
R3,001 - R4,000
62%
19%
GENDER RELATIVE TO MEAL PREPARATION
GENDER RELATIVE TO MEAL PREPARATION
100%
72%
94%
100%
90%
90%
80%
80%
70%
70%
60%
60%
50%
50%
40%
40%
30%
30%
20%
20%
10%
10%
0%
0% COOK THEIR OWN MEALS
28% 6%
DO NOT COOK THEIR OWN MEALS
COOK THEIR OWN MEALS
DO NOT COOK THEIR OWN MEALS 56
NUMBER OF MEALS MAINEATEN MEALS EATEN NUMBER OF MAIN PER DAY
PER DAY
49%
33%
11%
8% 57 57
FOOD ITEMS REPORTED TOFROM BE MISSING FOOD ITEMS REPORTED TO BE MISSING DIET
FROM DIET
57% 26% 17%
58
WHAT RESPONDENTS WOULD BUY WHAT PARTICIPANTS WOULD BUY IF GIVEN R100
3%
4% 4%
IF GIVEN R100
2%
4%
32%
7% 11%
7%
FRUIT & VEG
11% 8%
8% EGGS
59 59
RELATIONSHIP BETWEEN HOUSEHOLD MONTHLY INCOME AND WHERE FOOD IS PURCHASED RELATIONSHIP BETWEEN HOUSEHOLD MONTHLY INCOME & WHERE FOOD IS PURCHASED
7% 16% SPAZA
Household monthly income:
< R999
15%
8% 16% 48%
HOT FOOD VENDOR
LARGE GROCERY STORE
15%
Household monthly income:
R2,001 - R3,000
14% TSHISANYAMA
R1,000 - R2,000
16%
14% 9%
FRUIT & VEG STALL
Household monthly income:
45%
15% 8% 18% 47%
15%
Household monthly income:
R3,001 - R4,000
41%
13% 20%
It should be noted that while the food purchased at Spaza shops decreases by 7% when monthly income increases by four times, food purchased at large grocery stores only increases by 2% when monthly incomes increases by four times.
60
RELATIONSHIP BETWEEN BMI ANDMEALS EATEN PER DAY RELATIONSHIP BETWEEN BMI & NUMBER OF MAIN NUMBER OF MAIN MEALS EATEN PER DAY
5% OBESE (BMI: > 30)
40%
Number of main meals eaten per day:
9% 32%
Number of main meals eaten per day:
2
1
39% 21%
23%
OVERWEIGHT (BMI: 25 - 30)
4%
8% NORMAL WEIGHT (BMI: 18.5 - 25) Number of main meals eaten per day:
32%
3
UNDERWEIGHT (BMI: < 18.5)
31%
Number of main meals eaten per day:
31%
40% 20% 61 61
27%
4
38%
RELATIONSHIP BETWEEN HOUSEHOLD MONTHLY INCOME RELATIONSHIP HOUSEHOLD MONTHLY INCOME & THE NUMBER OF MAIN AND THEBETWEEN NUMBER OF MAIN MEALS EATEN PER DAY MEALS EATEN PER DAY
1 MEAL PER DAY
7% 9%
7% 10%
Household monthly income:
Household monthly income:
< R999
2 MEALS PER DAY
48%
55%
13% 3 MEALS PER DAY
36%
2% 17%
11%
Household monthly income:
R2,001 - R3,000
4 MEALS PER DAY
40%
28%
R1,000 - R2,000
36%
40%
Household monthly income:
R3,001 - R4,000
41% 62
RELATIONSHIP BETWEEN MAIN MEALS EATEN PER DAY AND THE NUMBER OF HOUSEHOLD MEMBERS
RELATIONSHIP BETWEEN MAIN MEALS EATEN PER DAY AND THE NUMBER OF HOUSEHOLD MEMBERS
4% 16% 1 MEAL PER DAY
40%
Number of people in household:
Number of people in household:
1-2 people
3-4 people
39%
2 MEALS PER DAY
Number of people in household:
5-6 people
31%
51% 6% 11%
10% 10%
3 MEALS PER DAY
4 MEALS PER DAY
8% 9%
29%
50% 63 63
Number of people in household:
7-8 people
53%
30%
RELATIONSHIP BETWEEN OBESITY AND HOUSEHOLD MONTHLY INCOME RELATIONSHIP BETWEEN OBESITY & HOUSEHOLD MONTHLY INCOME
34%
HOUSEHOLD MONTHLY INCOME
HOUSEHOLD MONTHLY INCOME
< R999
R1,000 - R2,000
31%
R2,001 - R3,000
32% 33%
R3,001 - R4,000
0%
50% 64 64
ACTUAL BEHAVIOUR The following data was gleaned from individual food diaries kept by the study participants. Participants completed 10 days at a time, three times for a total of 30 days. The information tracked by the participants, was given to the field workers each 10-day period. It should be noted that the following graphs only record the frequency that particular foods were consumed and NOT the quantity or portion sizes.
65
DISTRIBUTION OF FOOD CATEGORIES ACROSS DIFFERENT MEALS OF THE DAY
DISTRIBUTION ACROSS FOOD CATEGORIES IN THE MORNING AM
DISTRIBUTION ACROSS FOOD CATEGORIES IN THE AFTERNOON
TOP 6 FOOD CATEGORIES CONSUMED IN THE EVENING
PM
AM
PM PM
PM
6%
4% 1% 1%
8% 2%
12%
11%
13%
42%
13%
24%
24%
candy and assorted sweets; Dairy: Yoghurt, cheese.
GRAIN
Grain: All Bran, Coco Pops cereal, Cornflakes, corn flour, maize cereals, oats, porridge, weet bix, pap, umvubo, bread, savoury pie, maize, pancakes, umnqusho, samp; Protein: Red meat, chicken, sea food, egg; Fruit: Apple, banana, orange, pear, guava, avocado, assorted other fruits; Vegetable: Potatoes, tomatoes, atchar, aubergine, parmigiana, broccoli, carrot, chakalaka, cucumber, mushroom, pepper, peri peri, soy mince, umfino, mixed vegetables; Snack: Potato and maize based snacks, baked goods, cookies, nuts, chocolate, candy and assorted sweets; Dairy: Yoghurt, cheese.
PROTEIN
44%
15%
75%
Grain: All Bran, Coco Pops cereal, Cornflakes, corn flour, maize cereals, oats, porridge, weet bix, pap, umvubo, bread, savoury pie, maize, pancakes, umnqusho, samp; Protein: Red meat, chicken, sea food, egg; Fruit: Apple, banana, orange, pear, guava, avocado, assorted other fruits; Vegetable: Potatoes, tomatoes, atchar, aubergine, parmigiana, broccoli, carrot, chakalaka, cucumber, mushroom, pepper, peri peri, soy mince, umfino, mixed vegetables; Snack: Potato and maize based snacks, baked goods, cookies, nuts, chocolate,
4% 1%
FRUIT
VEGETABLE
SNACK
Grain: All Bran, Coco Pops cereal, Cornflakes, corn flour, maize cereals, oats, porridge, porridge, weet bix, pap, umvubo, bread, savoury pie,'maize, pancakes, umnqusho, samp; Protein: Red meat, chicken, sea food, egg; Fruit: Apple, banana, orange, pear, guava, avocado, assorted other fruits; Vegetable: Potatoes, tomatoes, atchar, aubergine, parmigiana, broccoli, carrot, chakalaka, cucumber, mushroom, pepper, peri peri, soy mince, umfino, mixed vegetables; Snack: Potato and maize based snacks, baked goods, cookies, nuts, chocolate, candy and assorted sweets; Dairy: Yoghurt, cheese.
DAIRY
Grain: All bran, coco pops cereal, cornflakes, corn flour, maize cereals, oats, porridge, weet bix, pap, umvubo, bread, savoury pie, maize, pancakes, umnqusho, samp; Protein: Red meat, chicken, sea food, egg; Fruit: Apple, banana, orange, pear, guava, avocado, assorted other fruits; Vegetable: Potatoes, tomatoes, atchar, aubergine, parmigiana, broccoli, carrot, chakalaka, cucumber, mushroom, pepper, purl, soy mince, umfino, mixed vegetables; Snack: Potato and maize based snacks, baked goods, cookies, nuts, chocolate, candy and assorted sweets; Dairy: Yoghurt, cheese.
66 66
TOP 6 FOODS EATEN PER DAY
TOP 6 FOODS EATEN PER DAY
4%
14%
5% 7%
13%
10%
Porridge: Maize or oat based, prepared with hot water or milk. May be sweetened or flavoured, Gwinya: Deep-fried dough balls; Umngqusho: Made of mielies Porridge: Maize or oat based, prepared with hot water or milk. May be sweetened or flavoured; Gwinya: Deep-fried dough balls; Umngqusho: Made of stamp mielies (samp) (samp) with beans, butter and vegetables. with beans, butter, and vegetables.
67
PROCESSED AND UNPROCESSED FOOD CONSUMED AT DIFFERENT TIMES
14%
27%
29%
86%
73%
71%
Processed Foods: Foods whose original, natural state is manipulated or altered in some way; Unprocessed Foods: Typically includes fruit and vegetables. Note: This graph excludes meat products.
68
PROCESSED AND UNPROCESSED FOOD EATEN PER DAY
PROCESSED AND UNPROCESSED FOOD EATEN PER DAY
25%
75% Processed Foods: Foods whose original, natural state is manipulated or altered in some way; Unprocessed Foods: Typically includes fruit and vegetables. Note: This graph meat products. *Processed Foods:excludes foods whose original, natural state is manipulated or'altered in some way **Unprocessed Foods: Typically includes fruit and vegetables. Note: This graph excludes meat products.
69 69
TOP 6 FRUITS CONSUMED OVER 30 DAYS AS A PERCENTAGE OF TOTAL FRUIT CONSUMPTION
TOP 6 FRUITS CONSUMED OVER 30 DAYS AS A PERCENTAGE OF TOTAL FRUIT CONSUMPTION
39% 30%
14% 5% 4% 3%
Other: Apricot, berry, fruit salad, cherry, coconut, granadilla, lemon, naatjies, nectarine, paw-paw, pineapple, plum, fruit salad, strawberry, watermelon.
Other: apricot, berry, fruit salad, cherry, coconut, granadilla, lemon, naatjies, nectarine, paw paw, pineapple, plum, prune, fruit salad, strawberry, watermelon.
70 70
CONSUMPTION OF TOP 3 FRUITS AS A PERCENTAGE OF TOTAL FRUIT INTAKE OVER 30 DAYS BETWEEN CONSUMPTION CONSUMPTION OF OF TOP TOP 33 FRUITS FRUITS AS AS AA PERCENTAGE PERCENTAGE OF OF TOTAL TOTAL DIFFERENT AGE GROUPS
FRUIT FRUIT INTAKE INTAKE OVER OVER 3030 DAYS DAYS BETWEEN BETWEEN DIFFERENT DIFFERENT AGE AGE GROUPS GROUPS AGE: 11 - 20 YRS
AGE:AGE: 11 -11 20- YRS 20 YRS AGE: 21 - 30 YRS
AGE:AGE: 21 -21 30- YRS 30 YRS AGE: 31 - 40 YRS
AGE:AGE: 41 AGE: 31- -50 31 40YRS - YRS 40 YRS
AGE: > 51 YRS
AGE:AGE: 41 -41 50- YRS 50 YRS
35% 35%
24% 24%
15% 15%
43% 43%
36% 36%
9%9%
37% 37%
27% 27%
15% 15%
40% 40%
21% 21%
17% 17%
38% 38%
33% 33%
14% 14%
AGE:AGE: >51>51 YRSYRS
71
CONSUMPTION OF DIFFERENT FRUITS AS FRUITS A PERCENTAGE TOTAL FRUIT INTAKE OVER 30 FRUIT DAYS CONSUMPTION OF DIFFERENT AS AOF PERCENTAGE OF TOTAL BETWEEN WEIGHT & OBESE PARTICIPANTS INTAKENORMAL OVER 3O DAYS BETWEEN NORMAL WEIGHT AND OBESE RESPONDENTS
70%
60%
TOTAL FRUITS
60%
46%
50% 40% 30% 20% 10%
NORMAL WEIGHT
38%
OBESE
31% 20% 13% 4%
7%
4%
7%
3% 5%
2% 3%
2% 4%
0%
Other: apricot, berry, fruit salad, cherry, coconut, granadilla, lemon, naartjies, nectarine, paw-paw, pineapple, plum, prune, strawberry, watermelo
Other: Apricot, berry, fruit salad, cherry, coconut, granadilla, lemon, naartjies, nectarine, paw-paw, pineapple, plum, prune, strawberry, watermelon.
72
1% 1%
TOP 3 VEGETABLES CONSUMED OVER 30 DAYS AS A PERCENTAGE OF TOTAL VEGETABLES CONSUMED
43%
18.5%
Mixed Vegetables: Vegetables, salad, stir fry vegetables and also typically frozen prepackaged assorted vegetables.
73
11%
CONSUMPTION OF TOP 3OF VEGETABLES AS A PERCENTAGEAS OFAS TOTAL VEGETABLE INTAKE OVER 30 DAYS CONSUMPTION CONSUMPTION OF TOP TOP 3 VEGETABLES 3 VEGETABLES A PERCENTAGE A PERCENTAGE OFOF TOTAL TOTAL BETWEEN DIFFERENT AGE GROUPS
VEGETABLE VEGETABLE INTAKE INTAKE OVER OVER 3030 DAYS DAYS BETWEEN BETWEEN DIFFERENT DIFFERENT AGE AGE GROUPS GROUPS
35% 35%
17% 17%
14% 14%
AGE: 21 - 30 YRS
44% 44%
22% 22%
9%9%
AGE: 21 AGE:- 30 21YRS - 30 YRS AGE: 31 - 40 YRS
40% 40%
15% 15%
12% 12%
AGE: 41 - 50 YRS
42% 42%
17% 17%
10% 10%
AGE: > 51 YRS
43% 43%
18% 18%
10% 10%
AGE: 11 - 20 YRS
AGE: 11 AGE:- 20 11YRS - 20 YRS
AGE: 31 AGE:- 40 31YRS - 40 YRS
AGE: 41 AGE:- 50 41YRS - 50 YRS
AGE: >51 AGE: YRS >51 YRS
MIXED MIXED ESTABLES BL GE VEGETA VE
Mixed Vegetables: Vegetables, salad, stir fry vegetables and also typically frozen prepackaged assorted vegetables.
74 74
CONSUMPTION OF DIFFERENT VEGETABLES AS A PERCENTAGE OF TOTAL VEGETABLE INTAKE OVER 30 CONSUMPTION OF DIFFERENT FRUITS AS A PERCENTAGE OF TOTAL FRUIT CONSUMPTION OF DAYS DIFFERENT VEGETABLES ASWEIGHT A PERCENTAGE OF TOTAL VEGETABLE DAYS BETWEEN NORMAL WEIGHT & OBESE PARTICIPANTS INTAKE OVER 3O BETWEEN NORMAL AND OBESE RESPONDENTS
INTAKE OVER 3O DAYS BETWEEN NORMAL WEIGHT AND OBESE RESPONDENTS
80%
70%
60%
70%
TOTAL VEGETABLES
60%
61%
60%
46%
50%
50%
40% 40%
30%
NORMAL WEIGHT NORMAL WEIGHT
38% 41%
OBESE
31%
30%
20%
OBESE
19%
26%
20% 13%
20%
18%
12%
10% 10%
17% 9%7%
4%
7% 4% 6% 6%
5% 7% 3% 6%
0% 0%
K OO
K OO
MIXED VEGGIES
VEGGIE SOUP
Other: apricot, berry, fruit salad, cherry, coconut, granadilla, lemon, naartjies, nectarine, paw-paw, pineapple, plum, prune, strawberry, watermelo
3% 2% 4%
7%
4% 2% 2%
1%
1% 1%
Mixed Vegetables: Vegetables, salad, stir fry vegetables and also typically frozen prepackaged assorted vegetables; Vegetable soup: Soup prepared with carrots, Mixed Vegetables: vegetables, salad, stir fry, vegetables; Vegetable soup: Soup prepared with carrots, potatoes, bones, split peas and fresh soup vegetable mix; potatoes, bones, split peas and fresh soup vegetabe mix; Other: Atchar, aubergine, parmigiana, avocado, broccoli, carrot, chakalaka, cucumber, guacomole, Other: atchar, aubergine, parmigiana, avocado, broccoli, carrot, chakalaka, cucumber, guacomole, mushrooms, pepper, peri-peri, soya mi nce, Umfino mushrooms, pepper, peri-peri, soya mince, umfuno.
75 75
CONSUMPTION OF DIFFERENT PROTEINS AS A PERCENTAGE OF PROTEINS TOTALASPROTEIN INTAKE DAYS CONSUMPTION OF DIFFERENT A PERCENTAGE OF TOTALOVER PROTEIN 30 INTAKE OVER 30 DAYS
64%
13% EGGS
12% 9%
Red Meat: beef, pork, and mutton products. *Beef and mutton products.
76
CONSUMPTION OF TOP 5 PROTEINS AS A PERCENTAGE OF TOTAL PROTEIN INTAKE OVER 30 DAYS ACROSS DIFFERENT AGE GROUPS
AGE: 11 - 20 YRS
70%
10%
10%
7%
3%
AGE: 21 - 30 YRS
63%
13%
13%
9%
2%
AGE: 31 - 40 YRS
62%
14%
11%
10%
3%
AGE: 41 - 50 YRS
68%
11%
11%
8%
2%
AGE: > 51 YRS
60%
15%
14%
9%
2%
RED MEAT
EGGS
CHICKEN
FISH
PORK
77
CONSUMPTION OF DIFFERENT PROTEINS FRUITS AS A PERCENTAGE OF TOTAL PROTEIN OVER 30 DAYS CONSUMPTION OF DIFFERENT AS A PERCENTAGE OFINTAKE TOTAL FRUIT BETWEEN WEIGHT AND OBESE PARTICIPANTS INTAKE NORMAL OVER 3O DAYS BETWEEN NORMAL WEIGHT AND OBESE RESPONDENTS
70%
TOTAL PROTEINS
25% 60%
24% 25% 60% 19% 19% 46%
50% 20% 40% 15%
NORMAL WEIGHT
38% 31%
30% 10% 20%
12%
10%20%
12%
13% 11%
10%
13%
10% 5%
OBESE
4%
7%
4%
7%
7%
8%
7%
3% 5%
6% 4% 4% 2% 3%
0%
2% 3%4% 2%
1% 1% 1% 1%
0% UNSPECIFIED MEAT
PORK
EGGS
FRENCH POLONY
CHICKEN
FISH
SAUSAGES
Other: apricot, berry, fruit salad, cherry, coconut, granadilla, lemon, naartjies, nectarine, paw-paw, pineapple, plum, prune, strawberry, watermelo
Unspecified Meats: Participants did not record type of meat
78
LIVER
BEEF
TRIPE & OFFALS
CONSUMPTION OF DIFFERENT CATEGORIES TOP 4 SNACKS CONSUMED OVER 30 DAYS OF SNACKSAS A PERCENTAGE OF TOTAL SNACK IN TAKE OVER 30 DAYS
14%
16%
19%
51%
Maize based snack: Includes crackers, popcorn, Fritos, Nik Naks; Potato based snack: Includes cheese crisps, Pringles and other brands. Baked snack: Includes biscuits, doughnuts, cake, muffin; Sweets: Includes chocolate, pudding, Tempo, marshmallows
Maize based snack: Includes crackers, popcorn, Fritos, Nik Naks; Potato based snack: Includes cheese crisps, Pringles and other brands; Baked snack: Includes biscuits, doughnuts, cake, muffin; Sweets: Includes chocolate, pudding, Tempo, marshmallows
79
CONSUMPTION OF TOP 5 SNACKS AS A PERCENTAGE OF TOTAL SNACK INTAKE OVER 30 DAYS ACROSS DIFFERENT AGE GROUPS
50%
21%
19%
10%
0%
AGE: 21 - 30 YRS
51%
18%
17%
18%
2%
AGE: 31 - 40 YRS
45%
20%
17%
15%
3%
AGE: 41 - 50 YRS
57%
19%
11%
11%
2%
AGE: > 51 YRS
52%
18%
16%
12%
2%
MAIZE BAKED SNACK
POTATO BAKED SNACK
BAKED SNACK
SWEETS
OTHER
AGE: 11 - 20 YRS
Maize based snacks: Includes crackers, popcorn, fritos, nik naks, Potato based snack: Includes cheese, crisps, pringles and other brands; Sweets: Includes chocolate, pudding, mashmallows, Baked snack: Includes biscuits, doughnuts, cakes, muffin; Other: Other unclassified snacks.
80
NUMBER OF SNACKS EATEN PER MONTH BY WEIGHT TYPE NUMBER OF SNACKS EATEN PER MONTH BY WEIGHT TYPE
MAIZE BASED SNACK
48%
47%
54%
49%
POTATO BASED SNACK TO BASED SNACK
19%
28%
13%
19%
SWEETS
15%
7%
14%
12%
BAKED SNACK
15%
13%
17%
18%
OTHER
2%
4%
1%
2%
ZE BASED SNACK
WEETS
BAKED SNACK
OTHER
Maize based snacks: Includes crackers, popcorn, Fritos, Nik Naks, Potato based snack: Includes cheese, crisps, Pringles and other brands; Sweets: Includes
ize based snacks: includes crackers, popcorn, fritos, nik naks; Potato based snack: includes cheese crisps, pringles and other brands; Sweets: includes chocolate, pudding, mashmallows; chocolate, pudding, mashmallows,Other: Baked snack: Includes biscuits, doughnuts, cakes, muffin; Other: Other unclassified snacks. Other unclassified snacks ked snack:
81
30 DAYS AS A PERCENTAGE OF TOTAL BEVERAGE CONSUMPTION TOP 6 BEVERAGES CONSUMED OVER 30 DAYS AS A PERCENTAGE OF TOTAL BEVERAGE CONSUMPTION
9% 11% 13% 14% 18%
30% Milk: Includes pure milk as well as dairy blends; Soda: Appletiser, Coca Cola, Lemon Twist, Fanta, Ice Tea, Jive, Iron Brew, Schweppes, Sprite, Stoney, Twizza, Tonic; Milk: Includes pure milk as well as dairy blends; Soda: Appletiser, coke, Cool Drink, soda, Lemon Twist, Fanta, ice tea, Jive, Iron Brew, Juice: Includes fruit concentrates as well as fruit juices in different degrees of purity Schweppes, Sprite, Stoney, Twizza,tonic; Juice: Includes fruit concentrates as well as fruit juices in different degrees of purity
82
AVERAGE VOLUME OF POPULAR AVERAGE VOLUME OF POPULAR BEVERAGES CONSUMED BEVERAGES CONSUMED PERPER DAYDAY
44 ML 155 ML 159 ML 186 ML 188 ML 265 ML
510
ML
Soda: appletiser, coca cola, cool crink, soda, Brew, lemon twist, fanta, ice tea, jive, Sprite, iron brew, schweppes, stoney ginger beer, wizza, tonic. Includes fruit concentrates as well as fruit Soda: Appletiser, Coca Cola, Lemon Twist, Fanta, Ice Tea, Jive, Iron Schweppes, Stoney,sprite, Twizza, Tonic; Juice: Juice: includes fruit concentrates as well as fruit juices in different degrees of purity. juices in different degrees of purity.
83
CONSUMPTION OF POPULAR BEVERAGES ASBEVERAGES A PERCENTAGE TOTAL BEVERAGE OVER 30 CONSUMPTION CONSUMPTION OF OF POPULAR POPULAR BEVERAGES AS AS AOFPERCENTAGE A PERCENTAGE OFINTAKE OF TOTAL TOTAL DAYS BEVERAGE BETWEEN AGE GROUPS BEVERAGE INTAKE INTAKE OVER OVER 30 30 DAYS DAYS BETWEEN BETWEEN DIFFERENT DIFFERENT AGE AGE GROUPS GROUPS
AGE: 11 - 20 YRS
AGE: 11 AGE: - 2011YRS - 20 YRS AGE: 21 - 30 YRS
AGE: 21 AGE: - 3021YRS - 30 YRS
26% 26% 21% 21% 16% 16% 10% 10% 15% 15% 10% 10% 2%2% 32% 32% 16% 16% 15% 15% 12% 12% 12% 12% 9%9% 3%3%
AGE: 31 - 40 YRS
30% 30% 18% 18% 14% 14% 13% 13% 12% 12% 9%9% 3%3%
AGE: 31 AGE: - 4031YRS - 40 YRS AGE: 41 - 50 YRS
28% 28% 21% 21% 13% 13% 14% 14% 10% 10% 10% 10% 3%3%
AGE: >41 51- YRS AGE: AGE: 5041YRS - 50 YRS
31% 31% 18% 18% 15% 15% 13% 13% 12% 12% 10% 10% 3%3%
AGE: >51 AGE:YRS >51 YRS
Milk: includes Milk: includes pure milk pure as well milkas asdairy well as blends; dairy Soda: blends; appletiser, Soda: appletiser, coca cola, coca cool cola, drink, cool soda, drink, lemon soda,twist, lemon fanta, twist, icefanta, tea, jive, ice tea, ironjive, brew, iron schweppes, brew, schweppes, sprite, stoney sprite,ginger stoney beer, ginger beer,
twizza, twizza, Juice: tonic; includes Juice: includes fruit concentrates fruit concentrates as well as asfruit welljuices as fruit in juices different in different degrees degrees of purity; ofAlcoholic purity; Alcoholic Beverage: Beverage: umqombothi, wine, cider, gin, wine, beer, gin, irish beer, coffee, irishbrandy, coffee, brandy, vodka,Twizza, whiskey. vodka, whiskey. Milk: Includes pure milktonic; as well as dairy blends; Soda: Appletiser, Coca Cola, Lemon Twist, Fanta, Ice Tea, Jive,umqombothi, Ironcider, Brew, Schweppes, Sprite, Stoney, Tonic; Juice: Includes fruit concentrates as well as fruit juices in different degrees of purity. Alcoholic Beverage: Umqombothi, cider, wine, gin, beer, irish coffee, brand, vodka, whiskey.
84 84
CONSUMPTION OF DIFFERENT NON-ALCOHOLIC BEVERAGES IN LITRES BY WEIGHT CLASS OVER 30 DAYS
CONSUMPTION OF DIFFERENT NON-ALCOHOLIC BEVERAGES IN LITRES BY WEIGHT CLASS OVER 30 DAYS
WATER
SODA
WATER SODA JUICE
JUICE
TEA TEA
MILK MILK
COFFEE COFFEE
OTHER OTHER
13.6L 7.6L 5.0L 4.5L 4.0L 3.9L 0.4L
12.6L 7.3L 5.3L 4.9L 3.3L 4.3L 1.0L
14.9L 8.0L 5.2L 5.8L 5.5L 5.3L 0.4L
15.8L 7.5L 5.2L 6.2L 5.0L 4.2L 0.5L
Soda:Milk: appletiser, cocapure cola, milk cool drink, soda, lemon blends; twist, fanta, ice tea, jive, iron brew, sprite, stoneyIce ginger tonic; Schweppes, Juice: includesSprite, fruit concentrates as well Tonic; as fruit Includes as well as dairy Soda: Appletiser, Coke,schweppes, Lemon Twist, Fanta, Tea,beer, Jive,twizza, Iron Brew, Stoney, Twizza, juicesJuice: in differne degrees of purity; Other: mageu (made fromjuices fermented meali pap), energy of drinks, hot chocolate, phuzamandla (made from mealie and yeast) Includes fruit concentrates as well as fruit in different degrees purity
85
CONSUMPTION OF DIFFERENT ALCOHOLIC BEVERAGES IN LITRES BY WEIGHT CLASS OVER 30 DAYS
CONSUMPTION OF DIFFERENT ALCOHOLIC BEVERAGES IN LITRES BY WEIGHT CLASS OVER 30 DAYS
BEER
WINE
BEER
WINE
BRANDY
BRANDY
CIDER
CIDER
SPIRITS
SPIRITS
1.7L 0.2L 0.1L 0.1L 0.0L
2.3L 0.7L 0.1L 0.0L 0.1L
1.2L 0.2L 0.2L 0.1L 0.1L
0.9L 0.1L 0.1L 0.2L 0.0L
Brandy: Often drank together with beer or sodas so quantities are likely overstated; Spirits: smirnoff, whiskey, gin, unclassified vodka, unclassified liquor, irish coffee. Brandy: Often drank together with beer or sodas so quantities are likely overstated; Spirits: smirnoff, whiskey, gin, unclassified vodka, unclassified liquor, irish coffee
86
WHERE FOOD AND BEVERAGES ARE PURCHASED
1%
5%
9%
21%
29%
35% Spaza: Informal convenience shop, Large Grocery Store: Such as Shoprite or Pick ‘n Pay only; Hot Food Vendor: An informal kiosk that sells pre-cooked food; Fruit & Veg Stall: An open-air stall largely vegetables and fruit as well as small confectionary; Tshisanyama: Informal barbecue or braai typically located near a butchery to grill meat on an open fire.
87 87
TOP 6 FOODS PURCHASED AT THE SPAZA SHOP
TOP 6 FOODS PURCHASED AT THE SPAZA SHOP
27%
7%
7% 6%
12%
6% 7% Red Meat: Includes beef and mutton; Maize Based Snacks: Includes snacks such as popcorn, Fritos, Nik Naks and others; Samp: Dried, stamped, and chopped corn kernels.
88
TOP 6 FOODS PURCHASED AT LARGE TOP 6 FOODS PURCHASED AT LARGE GROCERY STORES
19%
GROCERY OUTLETS
17%
5%
11%
6%
10% Red Meat: Includes beef and mutton; Samp: Dried, stamped, and chopped corn kernels; Potatoes: Includes potatoes as well French fries.
89 89
TOP 6 BEVERAGES PURCHASED AT THE SPAZA SHOPS TOP 6 BEVERAGES PURCHASED AT THE
SPAZA SHOP
29%
18% 14% 13%
21%
3%
Soda: Appletiser, Coca Cola, Lemon Twist, Fanta, Ice Tea, Jive, Iron Brew, Schweppes, Sprite, Stoney Ginger Beer, Twizza, Tonic; Juice: Includes fruit concentrates as well as fruit juices in different degrees of purity.
90
TOP 6 BEVERAGES PURCHASED AT LARGE GROCERY CHAINS TOP BEVERAGES PURCHASED AT LARGE GROCERY STORES
33%
21%
4% 15%
12%
13% Soda: Appletiser, Coca Cola, Lemon Twist, Fanta, Ice Tea, Jive, Iron Brew, Schweppes, Sprite, Stoney Ginger Beer, Twizza, Tonic; Juice: Includes fruit concentrates as well as fruit juices in different degrees of purity.
91 91
MOTIVATION FOR BEHAVIOUR Once the 30 days of food diaries had been completed, each participant was interviewed by one of the researchers, usually in their homes, to glean a detailed understanding of what motivated their eating and purchasing behaviours. This part of the research attempted to gain a more in-depth understanding of what affected their behaviour and to understand their perceptions of various food and beverage products. In addition, these interviews also explored the relative importance of food and eating in comparison to a broader range of human behaviour. Note that some questions were repeated again from the ‘Perceptions of Behaviour’ section of this study to test consistency in the answers after the participants had spent 30 days thinking more deeply about their eating behaviour. 92 92
MAIN HOUSEHOLD DECISIONDECISION MAKER MAIN HOUSEHOLD
MAKER
?
31% 93
?
69%
MONTHLY HOUSEHOLD INCOME
56%
60%
50%
PERCENTAGE
40%
30%
23%
16%
20%
3%
10%
2%
0%
R0 - R999
R1,000 - R2,000
R2,001 - R3,000
R3,001 - R4,000
> R4,000
MONTHLY HOUSEHOLD INCOME The income distribution is not the same as the census principally because the categories used are different. However, the figures are very close although this information was gathered three years later.
94 94
GOVERNMENT HOUSING SUBSIDY* RECIPIENTS
GOVERNMENT/SOCIAL GRANT *SUBSIDY RECIPIENTS
86% * Individual housing subsidies are and available to low-income where an applicant wishes receive. to buy *This speaks broadly to government subsidies social grantshouseholds, that individuals said they The grants cover the gamut - health, housing and childcare. a residential property for the first time. It is not a cash pay-out, but is paid directly to a financial institution. Applicants with a household income of less than R3 500, are eligible for a subsidy of R96 362.
95 95
AVERAGE AVERAGE DAILY SPEND DAILYON SPEND AIRTIME ON AIRTIME AVERAGE DAILY SPEND ON AIRTIME
80%
PERCENTAGE
70%
71% 71% 80%
70%
60%
60%
50%
50%
40%
40%
30%
30%
20%
20%
10%
10%
0%
0%
R5 - R10
25%
25% 3%
R5 - R10R11 - R20
R11 - R20 R21 - R50
AVERAGE DAILY SPEND ON AIRTIME
96
3% 1%
1%
R21 - R50 R51 - R100
R51 - R100
FOOD PREPARATION RELATIVE TO GENDER
FOOD PREPARATION RELATIVE TO GENDER
24% 76%
97 97
KITCHEN APPLIANCES USED IN FOOD PREPARATION
KITCHEN APPLIANCES USED IN FOOD PREPARATION
4% 1% 1% 20%
74%
98
FOOD STORAGE AREAS
3%
15% 2%
31%
49% 99
COOKING METHODS USED
38%
33%
4%
4%
11%
7% 100
6%
PERCEPTIONS OF THE HEALTHIEST METHODS OF PREPARING FOOD
63%
9%
4%
2%
12%
7% 101
3%
PERCEPTIONS OF THE UNHEALTHIEST METHODS OF PREPARING FOOD
58%
7%
11%
7%
8%
2% 102
9%
FREQUENCY OF GOING TO BED HUNGRY IN THE LAST THREE MONTHS
FREQUENCY OF GOING TO BED HUNGRY IN THE LAST THREE MONTHS
71%
29% 103
MONEY) EACH MONTH TO FEED THEMSELVES PERCENTAGE WHO BORROW (FOOD OR MONEY) EACH MONTH TO FEED THEMSELVES
76% 104 104
ONCE
FREQUENCY WITH WHICH FOOD FREQUENCY WITH WHICH FOOD WAS BORROWED IN THE LAST MONTH WAS BORROWED IN THE LAST MONTH
TWICE
THREE TIMES
MORE THAN THREE TIMES
5%
ONCE
TWICE
14%
5%
14% THREE TIMES
MORE THAN THREE TIMES
39%
42%
42% 105 105
39%
PEOPLE FROM WHOM FOOD IS BORROWED
1% 1% 2% 22%
27%
46% 106 106
ESPONDENTS GAVE FOR3% EATING 3%AGREE AGREE DISAGREE DISAGREE AGREE
%
90% 90% 97% 97% 94% 10% 3% 3% 10% 6%
90% 80% 90% 80% 94% 94%
80% 80% 90%
10% 20% 10% 6% 6% 20%
20% 20% 10%
90% 90% 78% 78% 80% 10% 10% 22% 22% 20% 96%
80% 80% 78% 56% 78% 56%
56% 56% 78%
20% 20% 22% 44% 22% 44%
44% 44% 22%
78% 78% 4% 56% 51% 51% 22% 22% 44% 49% 49%
56% 56%
DISAGREE
3%
SUE AGREE TYLE
%
6% 6% 3%
REASONS PARTICIPANTS GAVE FOR EATING
O PURSUE LIFESTYLE 97%
GREE
6% 3% 3% 6%
DISAGREE
90% DISAGREE
98%10% 2%
78% 22%
94%
96% 4%
30% 51% 51% 30% 44% 44%
30% 30% 51%
70% 49% 49% 70%
70% 70% 49%
93% 51% 51%
107
30% 30%
OFOF WHAT WHAT HEALTH HEALTH MEANS MEANS NTS' UNDERSTANDING 97% EALTH MEANS UNDERSTANDING OF WHAT HEALTH97% PARTICIPANTS’ MEANS 97%97% 94%94% AGREEAGREE DISAGREE DISAGREE 3% 3% AGREE DISAGREE 6% 6% 3% 3%
O PURSUE LIFESTYLE 97% 3%
SUE AGREE TYLE
GREE
%
%
94% DISAGREE 6%
98%
80% 2% 20%
78% 94% 22%
DISAGREE
94%94% 94% 94% 6%90% 6% 90% 6% 6%
97%97% 94% 3% 94% 94%3% 6% 6% 6% 94%94% 90% 6% 6% 80%80% 10%
96%
20%20% 80%80% 78% 4% 20% 20%78% 78% 96% 22% 22%22% 78%78% 4% 56% 93% 22%22% 44% 51%51%
10%10% 90%90% 80% 80% 10%10% 78%78% 20% 20% 22%22% 78%78% 78% 78% 22%22% 56% 56% 22% 22% 44%44% 56%56% 44% 51%44% 51% 108 30%30%
94% 94% 94% 3% 94% 6% 6% 6% 6% 94% 90% 90% 6% 80% 80% 10% 10% 20% 20% 80% 78% 78% 78% 78% 20% 22% 22% 22% 22%
90% 90% 6% 10% 10% 90% 10% 78% 78% 22% 22% 78% 56% 56% 22% 44% 44% 56%
78% 56% 56% 22% 51%44% 51%44%
44% 30% 30%
49% 49%
70% 70%
51% 30% 30% 49%
30% 70%
PAGES 115 - 120: PERCEPTIONS OF BODY WEIGHT Each participant of the study was shown the following images:
This self-perception data was then pooled, which provided the means for comparing it to the actual BMI data collected as part of the study to determine the difference between actual BMI and self perception.
109 109
FEMALE PERCEPTIONS OF WEIGHT FEMALE PERCEPTIONS OF WEIGHT
41%
45% 40% 35%
PERCENTAGE
30%
27%
NORMAL WEIGHT BMI: 18.5 - 25
24%
UNDERWEIGHT BMI: < 18.5
OVERWEIGHT BMI: 25 - 30
25%
8%
20% 15%
OBESE BMI: > 30
10% 5% 0% PERCEIVED WEIGHT
110 110
RELATIONSHIP BETWEEN PERCEIVED BODY WEIGHT & ACTUAL BMI FEMALES
49% 41%
60%
PERCENTAGE
50%
27% 19%
40%
30%
24%
29% 8%
3%
20%
10%
0%
UNDERWEIGHT UNDERWEIGHT (BMI: 18.5) ( 30)
When reviewing the participants’ perceptions of their weight and health it is imperative that an afro-centric lens is considered. The ‘Afro-centric aesthetic’ often runs counter to the dominant Western cultural values regarding health, weight and beauty. As such, the larger social, cultural and political context within which participants are making food choices and weight preferences greatly influences their self-perception.
111 111
MALE PERCEPTIONS OF WEIGHT MALE PERCEPTIONS OF WEIGHT
60%
PERCENTAGE
50%
52%
UNDERWEIGHT BMI: < 18.5
46%
NORMAL WEIGHT BMI: 18.5 - 25
40%
30%
20%
3%
OVERWEIGHT BMI: 25 - 30
10%
0% PERCEIVED WEIGHT
112
0%
OBESE BMI: > 30
RELATIONSHIP BETWEEN PERCEIVED BODY WEIGHT AND ACTUAL BMI OF MALES RELATIONSHIP BETWEEN PERCEIVED BODY WEIGHT & ACTUAL BMI OF MALES
63% 52%
46%
70%
60%
PERCENTAGE
50%
17%
40%
30%
8%
3%
20%
12% 0%
10%
0%
UNDERWEIGHT UNDERWEIGHT (BMI: (BMI R201
RELATIONSHIP WITH LOCAL SPAZA OWNER
RELATIONSHIP WITH LOCAL SPAZA OWNER
44%
56% 138 138
CUSTOMER LOYALTY TO LOCAL SPAZA SHOPS CUSTOMER LOYALTY TO LOCAL SPAZA SHOPS
46%
54%
139 139
GENDER PROFILE OF CUSTOMERS
54%
SHOP
140 140
46%
AVERAGE CUSTOMER AGE DISTRIBUTION
8%
19%
21%
31% AGE: 21 - 30 YRS
AGE: 11 - 20 YRS
21% AGE: 31 - 40 YRS
AGE: 6 - 10 YRS
AGE: 1- 5 YRS
141
CUSTOMER RETAIL BEHAVIOUR IN ALL FOUR SPAZA SHOPS CUSTOMER RETAIL BEHAVIOUR IN ALL FOUR SPAZA SHOPS
90%
80%
70%
PERCENTAGE
60%
50%
40%
30%
20%
10%
0%
142 142
TOP 5 PRODUCTS REPORTEDLY PURCHASED AT SPAZA
CIGARETTES
CIGARETTES
CIGARETTES
CIGARETTES
CIGARETTES
CIGARETTES
CIGARETTES
CIGARETTES
CIGARETTES
CIGARETTES
CIGARETTES
CIGARETTES
CIGARETTES
CIGARETTES
CIGARETTES
CIGARETTES
CIGARETTES
42%
CIGARETTES
CIGARETTES
CIGARETTES
CIGARETTES
CIGARETTES
CIGARETTES
28% BREAD
20% AIRTIME
CRISPS
CRISPS
CRISPS
CRISPS
6%
CRISPS
143 143
5%
BEER
POPULAR PRODUCTS SPAZA OWNERS REPORTED SELLING
POPULAR PRODUCTS SPAZA OWNER REPORTED SELLING
6%
20%
6%
JUICE****
CRISPS
7%
13%
7% 7%
13% 7%
****Includes fruit concentrates as well as fruit juices in different degrees of purity ***Non alcoholic fermented beverage **Crushed maize meal *Porridge
144 144
HAVE BEEN SOLD BY OWNERS FRUITS & VEGETABLES REPORTED TO HAVE BEEN SOLD BY SPAZA OWNERS
145 145
CLOSING REMARKS What has been discovered through this research both affirms previous studies and unearths a range of new information about food consumption behaviours, beliefs and values amongst the urban poor. It supports the idea that until the desires, aspirations, attachments, and motivations of any community are understood, sustainable solutions to their challenges will not emerge.
146
Our intention remains that the information and knowledge
security, health, and education ecosystems to make more
generated out of this research will support policy,
informed decisions.
programmes and solutions to the food security challenges facing South Africa.
It was important for us to stay true to our motivations of testing the everyday urbanism theories in practice. What
We have deliberately not provided commentary or
has been discovered through this research both affirms
developed any firm conclusions about the behaviours and
previous studies and unearths a range of new information
patterns of participants that emerged from this data. This
about food consumption behaviours, beliefs and values
choice is principally, because we are not food security
amongst the urban poor. It supports the idea that until
experts nor do we hold an intimate understanding, beyond
the desires, aspirations, attachments, and motivations of
this research, of the environment from which this data was
any community are understood, sustainable solutions to
drawn. Our aspiration is that this body of research will
their challenges will not emerge.
support the needs of others better placed within the food
147
ACKNOWLEDGEMENTS The Africa Centre would like to extend its deepest gratitude to the following people for their contributions to this project: Literature Review: Etai Even-Zahav, Elena Geuking & Luke
Data Entry: Taguekou Alexie, Edwin Uzochukwu Anowi,
Metelerkamp (Sustainability Institute)
Franklin Ondah Awaseh, Adedapo Awotidebe, Nkemngu Awungiia, Juveta Ayuk, Modele Bitkeu De Bitnga, Thuliswa
Statistical Analysis: Brighton Chipuka, Guillaum Doree, Luke
Bulana, Jean-Paul De Lange, Rickael Easton, Rosemary Enjema,
Fostvedt (Iowa State University), Pascal Fröhlicher, Dr. Yoram
Ebot Enih, Samuel Enow, Tulisa Gantsho, Brian Githungo,
Gat, Jorieke Haarhuis, Tsakane Lesea, Garreth Lombard, Adela
Ethell Cikizwa Gqirhana, Kenechukwu Maduka Ikebuaku,
Novotna & Gregor Schueler
Chouriya Lougue Kabore, Gaelle Fitong Ketchiwou, Arlette Molako Leufak, Claudia Mukong, Onorine Mujih, Olusola Saibu,
Field Research: Brighton Chipuka, Felicity Mbambani, Claire
Varlorine Tah, Yves Tchakounte, Zubayr Van Wyk led by
Mollatt, Siyamthanda Mrwebi, Alecia Msila, Nosisi Mzingelwa,
Nguatem Michael Belebema (University of the Western Cape)
Charity Nonhlanhla Ndimande, Nomzamo Nokoyo, Africa Tole & Anele Zenzile
148
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